Search ga_ls9c_ard_3 whole collection

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud pixels. For these ARD products, this value comes from the Fmask algorithm. to (exclusive):

Time when dataset was created (processed) From

Time when dataset was created (processed) to (exclusive)

The raw CRS string as it appears in metadata:

One of - final|interim|nrt (near real time):

ID of a dataset type:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. from:

Ground sampling distance of the sensor’s best resolution band in metres; represents the size (or spatial resolution) of one pixel. to (exclusive):

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north from:

The azimuth angle of the sun at the moment of acquisition, in degree units measured clockwise from due north to (exclusive):

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. from:

The elevation angle of the sun at the moment of acquisition, in degree units relative to the horizon. to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear land pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains cloud shadow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear snow pixels according to the Fmask algorithm to (exclusive):

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm from:

The proportion (from 0 to 100) of the dataset's valid data area that contains clear water pixels according to the Fmask algorithm to (exclusive):

File format (GeoTiff, NetCDF):

GQA Circular error probable (90%) from:

GQA Circular error probable (90%) to (exclusive):

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the absolute values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the total GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Absolute value of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Circular error probable (90%) of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals after removal of outliers, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Mean of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the x-axis (east-to-west) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) from:

Standard Deviation of the values of the y-axis (north-to-south) GCP residuals, in pixel units based on a 25 metre resolution reference image (i.e. 0.2 = 5 metres) to (exclusive):

Dataset UUID:

User who indexed the dataset:

When dataset was indexed:

Label:

A Landsat Collection 1 Level-1 product identifier including the Collection processing levels, processing date, collection number, and collection tier category (e.g. ‘LE07_L1TP_098084_20210307_20210308_02_RT’) :

A Landsat scene ID including WRS path and row, year and day, ground station identifier and archive version number (e.g. ‘LC80900852021066LGN00’) :

Latitude range from:

Latitude range to (exclusive):

Longitude range from:

Longitude range to (exclusive):

Full metadata document:

Metadata type name of dataset:

ID of a metadata type:

Spatial reference code from the provider. For Landsat region_code is a scene path row: '{:03d}{:03d}.format(path,row)' For Sentinel it is MGRS code. In general it is a unique string identifier that datasets covering roughly the same spatial region share. :

Acquisition time range From

Acquisition time range to (exclusive)

Dataset URI:

Add field

First 100 results (query limit)

Time (local)	Label
2021-11-08 10:01:01	ga_ls9c_ard_3-2-1_097084_2021-11-08_final.stac-item
2021-12-07 11:36:38	ga_ls9c_ard_3-2-1_112084_2021-12-07_final.stac-item
2021-12-09 11:19:04	ga_ls9c_ard_3-2-1_110071_2021-12-09_final.stac-item
2021-12-09 11:21:04	ga_ls9c_ard_3-2-1_110076_2021-12-09_final.stac-item
2021-12-13 09:21:48	ga_ls9c_ard_3-2-1_090087_2021-12-12_final.stac-item
2021-12-18 09:35:07	ga_ls9c_ard_3-2-1_093074_2021-12-18_final.stac-item
2021-12-19 11:58:04	ga_ls9c_ard_3-2-1_116076_2021-12-19_final.stac-item
2021-12-27 11:05:50	ga_ls9c_ard_3-2-1_108069_2021-12-27_final.stac-item
2021-12-28 11:51:06	ga_ls9c_ard_3-2-1_115074_2021-12-28_final.stac-item
2021-12-31 09:07:01	ga_ls9c_ard_3-2-1_088081_2021-12-30_final.stac-item
2022-01-03 11:18:00	ga_ls9c_ard_3-2-1_109084_2022-01-03_final.stac-item
2022-01-14 09:22:55	ga_ls9c_ard_3-2-1_090090_2022-01-13_final.stac-item
2022-01-20 11:58:03	ga_ls9c_ard_3-2-1_116076_2022-01-20_final.stac-item
2022-01-29 11:52:41	ga_ls9c_ard_3-2-1_115078_2022-01-29_final.stac-item
2022-02-15 10:56:11	ga_ls9c_ard_3-2-1_106076_2022-02-15_final.stac-item
2022-02-20 09:33:48	ga_ls9c_ard_3-2-1_093071_2022-02-20_final.stac-item
2022-02-27 11:19:58	ga_ls9c_ard_3-2-1_110074_2022-02-27_final.stac-item
2022-03-10 09:27:42	ga_ls9c_ard_3-2-1_091087_2022-03-09_final.stac-item
2022-03-28 09:14:03	ga_ls9c_ard_3-2-1_089084_2022-03-27_final.stac-item
2022-04-30 09:51:56	ga_ls9c_ard_3-2-1_096071_2022-04-30_final.stac-item
2022-05-04 09:32:22	ga_ls9c_ard_3-2-1_092084_2022-05-04_final.stac-item
2022-05-11 09:40:05	ga_ls9c_ard_3-2-1_093088_2022-05-11_final.stac-item
2022-05-15 09:16:06	ga_ls9c_ard_3-2-1_089090_2022-05-14_final.stac-item
2022-05-22 09:17:24	ga_ls9c_ard_3-2-1_090078_2022-05-21_final.stac-item
2022-06-16 10:52:14	ga_ls9c_ard_3-2-1_105083_2022-06-16_final.stac-item
2022-06-20 10:25:13	ga_ls9c_ard_3-2-1_101077_2022-06-20_final.stac-item
2022-06-21 11:05:43	ga_ls9c_ard_3-2-1_108070_2022-06-21_final.stac-item
2022-06-27 10:27:57	ga_ls9c_ard_3-2-1_102068_2022-06-27_final.stac-item
2022-07-12 09:45:49	ga_ls9c_ard_3-2-1_095071_2022-07-12_final.stac-item
2022-07-23 11:11:05	ga_ls9c_ard_3-2-1_108083_2022-07-23_final.stac-item
2022-07-24 10:10:17	ga_ls9c_ard_3-2-1_099070_2022-07-24_final.stac-item
2022-08-06 11:20:25	ga_ls9c_ard_3-2-1_110075_2022-08-06_final.stac-item
2022-08-13 11:26:16	ga_ls9c_ard_3-2-1_111074_2022-08-13_final.stac-item
2022-08-22 09:41:15	ga_ls9c_ard_3-2-1_094074_2022-08-22_final.stac-item
2022-08-22 11:23:19	ga_ls9c_ard_3-2-1_110082_2022-08-22_final.stac-item
2022-09-02 09:27:30	ga_ls9c_ard_3-2-1_091086_2022-09-01_final.stac-item
2022-09-05 11:32:06	ga_ls9c_ard_3-2-1_112073_2022-09-05_final.stac-item
2022-09-05 11:34:53	ga_ls9c_ard_3-2-1_112080_2022-09-05_final.stac-item
2022-09-10 10:15:45	ga_ls9c_ard_3-2-1_099083_2022-09-10_final.stac-item
2022-09-11 09:21:20	ga_ls9c_ard_3-2-1_090086_2022-09-10_final.stac-item
2022-09-16 11:17:13	ga_ls9c_ard_3-2-1_109082_2022-09-16_final.stac-item
2022-09-18 11:00:05	ga_ls9c_ard_3-2-1_107070_2022-09-18_final.stac-item
2022-09-25 11:06:42	ga_ls9c_ard_3-2-1_108071_2022-09-25_final.stac-item
2022-09-26 10:15:28	ga_ls9c_ard_3-2-1_099082_2022-09-26_final.stac-item
2022-09-28 09:59:31	ga_ls9c_ard_3-2-1_097073_2022-09-28_final.stac-item
2022-10-04 09:25:14	ga_ls9c_ard_3-2-1_091080_2022-10-03_final.stac-item
2022-10-14 09:58:24	ga_ls9c_ard_3-2-1_097070_2022-10-14_final.stac-item
2022-10-18 09:40:29	ga_ls9c_ard_3-2-1_093087_2022-10-18_final.stac-item
2022-10-25 11:19:10	ga_ls9c_ard_3-2-1_110071_2022-10-25_final.stac-item
2022-10-28 11:51:39	ga_ls9c_ard_3-2-1_115075_2022-10-28_final.stac-item
2022-11-02 10:30:29	ga_ls9c_ard_3-2-1_102073_2022-11-02_final.stac-item
2022-11-07 10:46:39	ga_ls9c_ard_3-2-1_105067_2022-11-07_final.stac-item
2022-11-08 09:52:14	ga_ls9c_ard_3-2-1_096070_2022-11-08_final.stac-item
2022-11-16 09:06:48	ga_ls9c_ard_3-2-1_088080_2022-11-15_final.stac-item
2022-11-26 11:21:09	ga_ls9c_ard_3-2-1_110076_2022-11-26_final.stac-item
2022-11-29 11:51:38	ga_ls9c_ard_3-2-1_115075_2022-11-29_final.stac-item
2022-11-30 09:21:30	ga_ls9c_ard_3-2-1_090086_2022-11-29_final.stac-item
2022-12-01 09:59:10	ga_ls9c_ard_3-2-1_097072_2022-12-01_final.stac-item
2022-12-05 11:13:45	ga_ls9c_ard_3-2-1_109073_2022-12-05_final.stac-item
2022-12-07 11:00:36	ga_ls9c_ard_3-2-1_107071_2022-12-07_final.stac-item
2022-12-12 11:24:21	ga_ls9c_ard_3-2-1_110084_2022-12-12_final.stac-item
2022-12-16 10:54:50	ga_ls9c_ard_3-2-1_106072_2022-12-16_final.stac-item
2023-01-22 09:38:44	ga_ls9c_ard_3-2-1_093083_2023-01-22_final.stac-item
2023-01-24 09:27:13	ga_ls9c_ard_3-2-1_091085_2023-01-23_final.stac-item
2023-01-24 09:28:01	ga_ls9c_ard_3-2-1_091087_2023-01-23_final.stac-item
2023-01-25 10:05:43	ga_ls9c_ard_3-2-1_098073_2023-01-25_final.stac-item
2023-01-26 09:13:18	ga_ls9c_ard_3-2-1_089081_2023-01-25_final.stac-item
2023-02-01 10:13:11	ga_ls9c_ard_3-2-1_099076_2023-02-01_final.stac-item
2023-02-02 10:54:52	ga_ls9c_ard_3-2-1_106072_2023-02-02_final.stac-item
2023-02-06 10:28:58	ga_ls9c_ard_3-2-1_102069_2023-02-06_final.stac-item
2023-02-08 10:22:12	ga_ls9c_ard_3-2-1_100083_2023-02-08_final.stac-item
2023-02-09 11:01:05	ga_ls9c_ard_3-2-1_107072_2023-02-09_final.stac-item
2023-03-12 10:19:03	ga_ls9c_ard_3-2-1_100076_2023-03-12_final.stac-item
2023-03-15 09:16:40	ga_ls9c_ard_3-2-1_089090_2023-03-14_final.stac-item
2023-03-31 10:46:58	ga_ls9c_ard_3-2-1_105069_2023-03-31_final.stac-item
2023-04-05 11:07:30	ga_ls9c_ard_3-2-1_108074_2023-04-05_final.stac-item
2023-04-05 11:09:29	ga_ls9c_ard_3-2-1_108079_2023-04-05_final.stac-item
2023-04-07 10:58:19	ga_ls9c_ard_3-2-1_106082_2023-04-07_final.stac-item
2023-04-12 11:13:13	ga_ls9c_ard_3-2-1_109073_2023-04-12_final.stac-item
2023-04-13 10:17:10	ga_ls9c_ard_3-2-1_100072_2023-04-13_final.stac-item
2023-04-23 10:55:49	ga_ls9c_ard_3-2-1_106076_2023-04-23_final.stac-item
2023-05-07 11:05:12	ga_ls9c_ard_3-2-1_108069_2023-05-07_final.stac-item
2023-05-17 10:04:32	ga_ls9c_ard_3-2-1_098072_2023-05-17_final.stac-item
2023-05-17 10:07:20	ga_ls9c_ard_3-2-1_098079_2023-05-17_final.stac-item
2023-05-31 10:20:46	ga_ls9c_ard_3-2-1_100082_2023-05-31_final.stac-item
2023-06-18 10:06:16	ga_ls9c_ard_3-2-1_098077_2023-06-18_final.stac-item
2023-07-01 09:36:18	ga_ls9c_ard_3-2-1_093079_2023-07-01_final.stac-item
2023-07-01 11:17:11	ga_ls9c_ard_3-2-1_109084_2023-07-01_final.stac-item
2023-07-20 10:03:21	ga_ls9c_ard_3-2-1_098069_2023-07-20_final.stac-item
2023-07-21 09:15:42	ga_ls9c_ard_3-2-1_089089_2023-07-20_final.stac-item
2023-08-09 11:20:04	ga_ls9c_ard_3-2-1_110075_2023-08-09_final.stac-item
2023-10-14 11:06:34	ga_ls9c_ard_3-2-1_108071_2023-10-14_final.stac-item
2023-10-15 10:15:45	ga_ls9c_ard_3-2-1_099083_2023-10-15_final.stac-item
2023-10-23 09:27:55	ga_ls9c_ard_3-2-1_091087_2023-10-22_final.stac-item
2023-10-23 09:28:19	ga_ls9c_ard_3-2-1_091088_2023-10-22_final.stac-item
2023-10-25 10:48:50	ga_ls9c_ard_3-2-1_105073_2023-10-25_final.stac-item
2023-10-30 11:08:31	ga_ls9c_ard_3-2-1_108076_2023-10-30_final.stac-item
2023-11-14 10:23:16	ga_ls9c_ard_3-2-1_101071_2023-11-14_final.stac-item
2023-11-17 10:53:47	ga_ls9c_ard_3-2-1_106070_2023-11-17_final.stac-item
2023-11-23 10:17:11	ga_ls9c_ard_3-2-1_100071_2023-11-23_final.stac-item

Return to ga_ls9c_ard_3 whole collection overview

ga_ls9c_ard_3: Geoscience Australia Landsat 9 Operational Land Imager and Thermal Infra-Red Scanner Analysis Ready Data Collection 3

Baseline satellite data

Inland water

Land and vegetation

Sea, ocean and coast

Hazards

Other products

All years